Machine learning (ML) has got considerable attention during the last years and is currently at the peak of the hype cycle. A number of applications of ML have been reported including drug discovery and synthesis planning. We have decided to apply ML to the available experimental data aiming to expand the REAL chemical space offered by Enamine. Amide coupling is one of the widely-utilized transformations for the last stage functionalization. Herein, we report our results on the application of ML methods and extensive experimental validation one of the protocols of amide formation.

Expanding the synthetically feasible chemical space of amides to a billion of compounds

ACS Fall 2020 Virtual Meeting

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.